A system is provided for object localization in image data. The system includes an object localization framework comprising a plurality of object localization processes. The system is configured to receive an image comprising unannotated image data having at least one object in the image, access a first object localization process of the plurality of object localization processes, determine first bounding box information for the image using the first object localization process, wherein the first bounding box information comprises at least one first bounding box annotating at least a first portion of the at least one object in the image, and receive first feedback regarding the first bounding box information determined by the first object localization process. The system is further configured to persist the image with the first bounding box information or access a second object localization process based on the first feedback.
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2. The system of claim 1, wherein the first bounding box operation comprises utilizing the neural network to generate convolution layer heatmaps of the object in the one or more images.
6. The system of claim 1, wherein in response to the feedback being the first bounding box representing the object in the one or more images, outputting the first set of annotation data.
7. The system of claim 1, wherein the neural network based object localization framework is trained using an unsupervised learning operation with unannotated image data for a plurality of objects.
9. The method of claim 8, wherein the first bounding box operation comprises utilizing the neural network to generate convolution layer heatmaps of the object in the one or more images.
13. The method of claim 8, wherein in response to the first bounding box representing the object in the one or more images, outputting the first set of annotation data.
14. The method of claim 8, wherein the neural network based object localization framework is trained using an unsupervised learning operation with unannotated image data for a plurality of objects.
16. The non-transitory machine-readable medium of claim 15, wherein the first bounding box operation comprises utilizing the neural network to generate convolution layer heatmaps of the object in the one or more images.
20. The non-transitory machine-readable medium of claim 15, wherein in response to the feedback being the first bounding box representing the object in the one or more images, outputting the first set of annotation data.
21. The non-transitory machine-readable medium of claim 15, wherein the neural network based object localization framework is trained using an unsupervised learning operation with unannotated image data for a plurality of objects.
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May 10, 2021
April 23, 2024
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